Labeled satellite imagery for training machine learning models that predict the suitability of imagery for shoreline extraction.
A labeled dataset of Landsat, Sentinel, and Planetscope satellite visible-band images of coastal shoreline regions, consisting of folders of images that have been labeled as either suitable or unsuitable for shoreline detection using existing conventional approaches such as CoastSat (Vos and others, 2019) or CoastSeg (Fitzpatrick and others, 2024). These data are intended to be used as inputs to models that determine the suitability or otherwise of the image. These data are only to be used as a training and validation dataset for a machine learning model that is specifically designed for the task of determining the suitability of an image for the task of estimating the shoreline location.
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Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[ "010:12" ] |
| contactPoint |
{ "fn": "PCMSC Science Data Coordinator", "@type": "vcard:Contact", "hasEmail": "mailto:pcmsc_data@usgs.gov" } |
| description | A labeled dataset of Landsat, Sentinel, and Planetscope satellite visible-band images of coastal shoreline regions, consisting of folders of images that have been labeled as either suitable or unsuitable for shoreline detection using existing conventional approaches such as CoastSat (Vos and others, 2019) or CoastSeg (Fitzpatrick and others, 2024). These data are intended to be used as inputs to models that determine the suitability or otherwise of the image. These data are only to be used as a training and validation dataset for a machine learning model that is specifically designed for the task of determining the suitability of an image for the task of estimating the shoreline location. |
| distribution |
[ { "@type": "dcat:Distribution", "title": "Digital Data", "format": "XML", "accessURL": "https://doi.org/10.5066/P14MDKVJ", "mediaType": "application/http", "description": "Landing page for access to the data" }, { "@type": "dcat:Distribution", "title": "Original Metadata", "format": "XML", "mediaType": "text/xml", "description": "The metadata original format", "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.799a4c57-8bcd-40a9-91ec-26dc0c8b9be5.xml" } ] |
| identifier | http://datainventory.doi.gov/id/dataset/USGS_799a4c57-8bcd-40a9-91ec-26dc0c8b9be5 |
| keyword |
[ "CMHRP", "Climate Change", "ClimatologyMeteorologyAtmosphere", "Coastal and Marine Hazards and Resources Program", "Erosion", "Extreme Weather", "Hazards Planning", "Ocean Waves", "Oceans", "PCMSC", "Pacific Coastal and Marine Science Center", "Physical Habitats and Geomorphology", "Sea Level Rise", "Sea-level Change", "Storms", "U.S. Geological Survey", "USGS", "USGS:799a4c57-8bcd-40a9-91ec-26dc0c8b9be5", "coastal erosion", "sea level change", "waves" ] |
| modified | 2025-03-25T00:00:00Z |
| publisher |
{ "name": "U.S. Geological Survey", "@type": "org:Organization" } |
| spatial | 180.00000, -90.00000, -180.00000, 90.00000 |
| theme |
[ "geospatial" ] |
| title | Labeled satellite imagery for training machine learning models that predict the suitability of imagery for shoreline extraction. |
